This specification describes a method comprising selecting at least one content stream from a plurality of content streams based on at least one detected characteristic associated with the content streams or an intended viewer of the content streams, wherein each content stream is captured by a corresponding recording device and at least one of the plurality of content streams is not selected, and compressing data representing the at least one selected content stream such that the content of the at least one selected content stream has a lower quality compared to the content of the at least one non-selected content stream.

It is provided a method for detecting an object in a left view image and a right view image, comprising steps of receiving the left view image and the right view image; detecting a coarse region containing the object in one image of the left view image and the right view image; detecting the object within the detected coarse region in the one image; determining a coarse region in the other image of the left view image and the right view image based on the detected coarse region in the one image and offset relationship indicating position relationship of the object in a past left view image and a past right view image; and detecting the object within the determined coarse region in the other image.

The present disclosure provides an optical invisible device. The optical invisible device sequentially comprises along an incident direction of an optical path: a first microlens array for imaging, an imaging unit, a display screen, and a second microlens array for projecting content displayed by the display screen to the outside, and further comprises an image processing unit. In addition, there is further provided another optical invisible device, which comprises: a first microlens array for imaging, a first imaging unit, a first image processing unit, a first display screen, and a second microlens array that are located at a first side, and a third microlens array, a second imaging unit, a second image processing unit, a second display screen, and a fourth microlens array that are located at a second side.

System for controlling the loading or unloading a cable [2] or the like onto a drum [3], wherein the drum [3] has a known first rotation axis loading or unloading the cable, the system also comprises an imaging means [1] aimed at the cable [2] from a position at a distance from the drum rotation axis, the imaging means [1] being adapted to measure the direction of the cable [2] relative to the rotational axis of the drum. The imaging means can be constituted by a video camera.

A device and method of dimensioning using digital images and depth data is provided. The device includes a camera and a depth sensing device whose fields of view generally overlap. Segments of shapes belonging to an object identified in a digital image from the camera are identified. Based on respective depth data, from the depth sensing device, associated with each of the segments of the shapes belonging to the object, it is determined whether each of the segments is associated with a same shape belonging to the object. Once all the segments are processed to determine their respective associations with the shapes of the object in the digital image, dimensions of the object are computed based on the respective depth data and the respective associations of the shapes.

A mechanism is described for facilitating generation of voxel representations and assignment of trust metrics according to one embodiment. A method of embodiments, as described herein, includes detecting, by a computing device, a plurality of data sources hosting image capturing devices capable of capturing images of objects in a space, where the images are capable of being received by the computing device. The method may further include tagging trust metrics to the images based on credibility of the plurality of data sources, where a trust metrics to indicate veracity of a corresponding image. The method may further include aggregating the images into an aggregated image representation, and generating a voxel representation of the aggregated image representation such that the images are presented as voxel images, where veracities of the voxel images are secured based on tagging of the trust metrics to their corresponding images.

Two or more images are taken wherein during the image taking a focal sweep is performed. The exposure intensity is modulated during the focal sweep and done so differently for the images. This modulation provides for a watermarking of depth information in the images. The difference in exposure during the sweep watermarks the depth information differently in the images. By comparing the images a depth map for the images can be calculated. A camera system has a lens and a sensor and a means for performing a focal sweep and means for modulating the exposure intensity during the focal sweep. Modulating the exposure intensity can be done by modulating a light source or the focal sweep or modulating the transparency of a transparent medium in the light path.

Systems and methods for modeling electric vehicle towing are disclosed herein. An example method includes determining that a trailer is connected to a vehicle, generating a surface mapping of the trailer based on output of a sensor assembly of the vehicle, predicting a drag coefficient of the trailer based on the surface mapping, estimating a drag force based on the drag coefficient and the surface mapping, calculating an estimated range for the vehicle based on the drag force, and displaying the estimated range on a human machine interface of the vehicle.

Systems and methods for modeling electric vehicle towing are disclosed herein. An example method includes determining that a trailer is connected to a vehicle, generating a surface mapping of the trailer based on output of a sensor assembly of the vehicle, predicting a drag coefficient of the trailer based on the surface mapping, estimating a drag force based on the drag coefficient and the surface mapping, calculating an estimated range for the vehicle based on the drag force, and displaying the estimated range on a human machine interface of the vehicle.

A mobile device comprises: a mesh loader manages configured to download compressed mesh sequences from a remote server into a local storage buffer; a mesh decoder that is configured to decode compressed mesh sequences into frames of meshes in real-time; a mesh decoder manager that is configured to request compressed mesh sequences from the mesh loader and to request the mesh decoder to decode the compressed mesh sequences; a player manager that is configured to decode texture video and to request corresponding decoded mesh from the mesh decoder manager and to maintain synchronizations between requesting the corresponding decoded mesh and decoding the texture video; and a renderer that is configured to render, using a rendering engine, the decoded mesh on a canvas; and a camera controller that is configured to detect one or more user actions and control a hardware camera in accordance with the one or more user actions.